CLI Commands
Kubetorch offers a rich set of commands to offer you insight into running workloads at the individual and cluster level.
Because all workloads are running as services on Kubernetes, you can also use kubectl
if you prefer to interact with your services.
kt billing
Show a summary of vCPU and GPU usage
kt check
Run a comprehensive health check for a deployed service
kt config
Get or set your username, namespace, and desired Kubetorch installation source URL for services launched with Kubetorch
kt dashboard
Open Kubetorch dashboard with Grafana
kt debug
Start an interactive debugging session on the pod, which will connect to the debug server inside the service
kt describe
Show basic info for calling the service from outside the cluster
kt deploy
Deploy a Python file or module to Runhouse. This will deploy all functions and modules decorated with @kt.compute
in the file or module
kt list
See live services and resources that have been deployed with Kubetorch
kt logs <kt-service-name>
View the logs for a particular service
kt metrics
Open Grafana dashboard
kt queues
List pods that are currently queued
kt run
Build and deploy a kubetorch app that runs the provided CLI command. In order for the app to be deployed, the file being run must be a Python file specifying a kt.app
construction at the top of the file.
kt ssh <kt-service-name>
Directly work on the remote compute by SSHing in (to the head node if distributed)
kt status
Load service status details
kt teardown <kt-service-name>
Tears down all related resources to a particular service